Index

A

add_edge() (trilearn.graph.junction_tree.JunctionTree method) add_edges_from() (trilearn.graph.junction_tree.JunctionTree method) add_graph() (trilearn.graph.empirical_graph_distribution.GraphDistribution method)

add_sample() (trilearn.graph.trajectory.Trajectory method) all_dec_graphs() (in module trilearn.graph.decomposable) approximate() (in module trilearn.smc) approximate_cond() (in module trilearn.smc)

B

backward_jt_traj_sample() (in module trilearn.graph.junction_tree_collapser) backward_order_neigh_log_prob() (in module trilearn.set_process)

backward_order_neigh_set() (in module trilearn.set_process) backward_perm_traj_sample() (in module trilearn.set_process)

C

conditional_prob_dec() (in module trilearn.distributions.discrete_dec_log_linear) CondUniformGivenSizeJTDistribution (class in trilearn.distributions.sequential_junction_tree_distributions) CondUniformJTDistribution (class in trilearn.distributions.sequential_junction_tree_distributions) connect_a() (in module trilearn.graph.greenthomas) connect_b() (in module trilearn.graph.greenthomas) connect_c() (in module trilearn.graph.greenthomas)

connect_d() (in module trilearn.graph.greenthomas) connect_logprob() (in module trilearn.graph.greenthomas) connect_move() (in module trilearn.graph.greenthomas) connect_select_subsets() (in module trilearn.graph.greenthomas) connected_component_vertices() (trilearn.graph.junction_tree.JunctionTree method) connected_components() (trilearn.graph.junction_tree.JunctionTree method) cov_matrix() (in module trilearn.distributions.g_intra_class)

D

disconnect_a() (in module trilearn.graph.greenthomas) disconnect_b() (in module trilearn.graph.greenthomas) disconnect_c() (in module trilearn.graph.greenthomas) disconnect_d() (in module trilearn.graph.greenthomas) disconnect_get_CXCY() (in module trilearn.graph.greenthomas)

disconnect_get_neighbors() (in module trilearn.graph.greenthomas) disconnect_logprob_a() (in module trilearn.graph.greenthomas) disconnect_logprob_bcd() (in module trilearn.graph.greenthomas) disconnect_move() (in module trilearn.graph.greenthomas) disconnect_select_subsets() (in module trilearn.graph.greenthomas)

E

empirical_distribution() (trilearn.graph.trajectory.Trajectory method) est_dec_max_clique_size() (in module trilearn.smc)

est_log_norm_consts() (in module trilearn.smc) est_n_dec_graphs() (in module trilearn.smc) est_parameters() (in module trilearn.distributions.discrete_dec_log_linear)

F

forest_induced_by_sep() (in module trilearn.graph.junction_tree) fresh_copy() (trilearn.graph.junction_tree.JunctionTree method) from_json() (trilearn.graph.empirical_graph_distribution.GraphDistribution method) (trilearn.graph.trajectory.Trajectory method)

from_json_file() (in module trilearn.graph.graph) from_prufer() (in module trilearn.graph.junction_tree)

G

gaussian_marginal_log_likelihood() (in module trilearn.distributions.gaussian_graphical_model) gen_AR_graph() (in module trilearn.graph.decomposable) gen_backward_order_neigh() (in module trilearn.set_process) gen_order_neigh() (in module trilearn.set_process) gen_prec_mat() (in module trilearn.auxiliary_functions) get_adjvec_trajectory() (trilearn.graph.trajectory.Trajectory method) get_all_counts() (in module trilearn.distributions.discrete_dec_log_linear) get_json_model() (trilearn.distributions.sequential_junction_tree_distributions.GGMJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.LogLinearJTPosterior method) get_marg_counts() (in module trilearn.auxiliary_functions)

get_separators() (trilearn.graph.junction_tree.JunctionTree method) get_smc_trajs() (in module trilearn.smc) get_subtree_nodes() (in module trilearn.graph.junction_tree_expander) get_traj() (in module trilearn.smc) GGMJTPosterior (class in trilearn.distributions.sequential_junction_tree_distributions) graph() (in module trilearn.graph.junction_tree) graph_diff_trajectory_df() (trilearn.graph.trajectory.Trajectory method) graph_to_tuple() (in module trilearn.graph.graph) GraphDistribution (class in trilearn.graph.empirical_graph_distribution) group_trajectories_by_setting() (in module trilearn.auxiliary_functions)

H

hash_graph() (in module trilearn.graph.graph)

heatmap() (trilearn.graph.empirical_graph_distribution.GraphDistribution method) hyperconsistent_cliques() (in module trilearn.distributions.discrete_dec_log_linear)

I

induced_subtree_nodes() (in module trilearn.graph.junction_tree) init_model() (trilearn.distributions.sequential_junction_tree_distributions.GGMJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.LogLinearJTPosterior method)

init_model_from_json() (trilearn.distributions.sequential_junction_tree_distributions.GGMJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.LogLinearJTPosterior method) is_junction_tree() (in module trilearn.graph.junction_tree) is_pos_def() (in module trilearn.auxiliary_functions)

J

jt_to_prufer() (in module trilearn.graph.junction_tree)

junction_tree() (in module trilearn.graph.decomposable) JunctionTree (class in trilearn.graph.junction_tree)

L

l1_loss() (in module trilearn.auxiliary_functions) l2_loss() (in module trilearn.auxiliary_functions) ll() (trilearn.distributions.sequential_junction_tree_distributions.CondUniformGivenSizeJTDistribution method) (trilearn.distributions.sequential_junction_tree_distributions.CondUniformJTDistribution method) ll_complete_set_ratio() (in module trilearn.distributions.discrete_dec_log_linear) ll_diff() (trilearn.distributions.sequential_junction_tree_distributions.GGMJTPosterior method) locals_to_joint_prob_table() (in module trilearn.distributions.discrete_dec_log_linear) log_count_origins() (in module trilearn.graph.junction_tree_collapser) log_likelihood() (in module trilearn.distributions.gaussian_graphical_model) (trilearn.distributions.sequential_junction_tree_distributions.GGMJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.LogLinearJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.UniformJTDistribution method) (trilearn.graph.trajectory.Trajectory method) log_likelihood_diff() (trilearn.distributions.sequential_junction_tree_distributions.LogLinearJTPosterior method) log_likelihood_partial() (in module trilearn.distributions.discrete_dec_log_linear) (in module trilearn.distributions.gaussian_graphical_model) (trilearn.distributions.sequential_junction_tree_distributions.GGMJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.UniformJTDistribution method)

log_n_junction_trees() (in module trilearn.graph.junction_tree) (trilearn.graph.junction_tree.JunctionTree method) log_n_junction_trees_update_ratio() (in module trilearn.graph.junction_tree) log_norm_constant() (in module trilearn.distributions.dirichlet) (in module trilearn.distributions.wishart) log_norm_constant_multidim() (in module trilearn.distributions.dirichlet) log_nu() (in module trilearn.graph.junction_tree) (trilearn.graph.junction_tree.JunctionTree method) log_pdf() (in module trilearn.distributions.dirichlet) (in module trilearn.distributions.multivariate_students_t) (in module trilearn.graph.junction_tree_collapser) log_ratio() (trilearn.distributions.sequential_junction_tree_distributions.CondUniformGivenSizeJTDistribution method) (trilearn.distributions.sequential_junction_tree_distributions.CondUniformJTDistribution method) (trilearn.distributions.sequential_junction_tree_distributions.GGMJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.LogLinearJTPosterior method) (trilearn.distributions.sequential_junction_tree_distributions.SequentialJTDistribution method) (trilearn.distributions.sequential_junction_tree_distributions.UniformJTDistribution method) LogLinearJTPosterior (class in trilearn.distributions.sequential_junction_tree_distributions) logpdf() (in module trilearn.distributions.wishart)

M

maximum_likelihood_graph() (trilearn.graph.trajectory.Trajectory method) mode() (trilearn.graph.empirical_graph_distribution.GraphDistribution method) module trilearn.auxiliary_functions trilearn.distributions trilearn.distributions.dirichlet trilearn.distributions.discrete_dec_log_linear trilearn.distributions.g_intra_class trilearn.distributions.g_inv_wishart trilearn.distributions.gaussian_graphical_model trilearn.distributions.matrix_multivariate_normal trilearn.distributions.multivariate_students_t trilearn.distributions.sequential_junction_tree_distributions trilearn.distributions.wishart trilearn.graph.decomposable trilearn.graph.empirical_graph_distribution trilearn.graph.graph trilearn.graph.greenthomas trilearn.graph.junction_tree trilearn.graph.junction_tree_collapser trilearn.graph.junction_tree_expander trilearn.graph.subtree_sampler trilearn.graph.trajectory trilearn.mh_greenthomas trilearn.pgibbs trilearn.set_process trilearn.smc

N

n_junction_trees() (in module trilearn.graph.decomposable) (in module trilearn.graph.junction_tree) n_junction_trees_update() (in module trilearn.graph.junction_tree)

n_subtrees() (in module trilearn.graph.junction_tree) n_subtrees_aux() (in module trilearn.graph.junction_tree) naive_decomposable_graph() (in module trilearn.graph.decomposable) normalizing_constant() (in module trilearn.distributions.wishart)

O

order_neigh_log_prob() (in module trilearn.set_process)

order_neigh_set() (in module trilearn.set_process)

P

pdf() (in module trilearn.distributions.dirichlet) (in module trilearn.graph.junction_tree_expander) (in module trilearn.graph.subtree_sampler) (trilearn.graph.empirical_graph_distribution.GraphDistribution method) pdf_multidim() (in module trilearn.distributions.dirichlet) peo() (in module trilearn.graph.decomposable) (in module trilearn.graph.junction_tree) plot() (in module trilearn.graph.graph)

plot_adjmat() (in module trilearn.graph.graph) plot_graph_traj_statistics() (in module trilearn.auxiliary_functions) plot_heatmap() (in module trilearn.auxiliary_functions) plot_matrix() (in module trilearn.auxiliary_functions) plot_multiple_traj_statistics() (in module trilearn.auxiliary_functions) possible_origins() (in module trilearn.graph.junction_tree_collapser) possible_origins_and_sets() (in module trilearn.graph.junction_tree_collapser) prob_dec() (in module trilearn.distributions.discrete_dec_log_linear)

R

random_element_from_coll() (in module trilearn.auxiliary_functions) random_subset() (in module trilearn.auxiliary_functions) random_subtree() (in module trilearn.graph.subtree_sampler) random_tree_from_forest() (in module trilearn.graph.junction_tree) randomize() (in module trilearn.graph.junction_tree) randomize_at_sep() (in module trilearn.graph.junction_tree) read_all_trajectories_in_dir() (in module trilearn.auxiliary_functions)

read_file() (trilearn.graph.trajectory.Trajectory method) read_from_dict() (trilearn.graph.empirical_graph_distribution.GraphDistribution method) read_local_hyper_consistent_parameters_from_json_file() (in module trilearn.distributions.discrete_dec_log_linear) remove_edge() (trilearn.graph.junction_tree.JunctionTree method) remove_edges_from() (trilearn.graph.junction_tree.JunctionTree method) remove_node() (trilearn.graph.junction_tree.JunctionTree method) replace_node() (in module trilearn.graph.graph)

S

sample() (in module trilearn.distributions.discrete_dec_log_linear) (in module trilearn.distributions.g_intra_class) (in module trilearn.distributions.g_inv_wishart) (in module trilearn.distributions.matrix_multivariate_normal) (in module trilearn.graph.decomposable) (in module trilearn.graph.junction_tree) (in module trilearn.graph.junction_tree_collapser) (in module trilearn.graph.junction_tree_expander) sample_classification_datasets() (in module trilearn.auxiliary_functions) sample_cond_on_subtree_nodes() (in module trilearn.graph.junction_tree_expander) sample_dec_graph() (in module trilearn.graph.decomposable) sample_hyper_consistent_counts() (in module trilearn.distributions.discrete_dec_log_linear) sample_hyper_consistent_parameters() (in module trilearn.distributions.discrete_dec_log_linear) sample_joint_prob_table() (in module trilearn.distributions.discrete_dec_log_linear) sample_new() (in module trilearn.graph.junction_tree_collapser) sample_prob_table() (in module trilearn.distributions.discrete_dec_log_linear) sample_random_AR_graph() (in module trilearn.graph.decomposable) sample_trajectories_ggm() (in module trilearn.pgibbs) sample_trajectories_ggm_parallel() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) sample_trajectories_ggm_to_file() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) sample_trajectories_loglin() (in module trilearn.pgibbs) sample_trajectories_loglin_parallel() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs)

sample_trajectories_loglin_to_file() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) sample_trajectory() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) sample_trajectory_ggm() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) sample_trajectory_loglin() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) sample_trajectory_uniform() (in module trilearn.mh_greenthomas) separators() (in module trilearn.graph.decomposable) (in module trilearn.graph.junction_tree) SequentialJTDistribution (class in trilearn.distributions.sequential_junction_tree_distributions) set_sampling_method() (trilearn.graph.trajectory.Trajectory method) set_sequential_distribution() (trilearn.graph.trajectory.Trajectory method) set_time() (trilearn.graph.trajectory.Trajectory method) set_trajectory() (trilearn.graph.trajectory.Trajectory method) size() (trilearn.graph.trajectory.Trajectory method) smc_approximate_ggm() (in module trilearn.smc) smc_ggm_graphs() (in module trilearn.smc) spc1() (in module trilearn.auxiliary_functions) subtree_cond_pdf() (in module trilearn.graph.junction_tree_expander) subtree_induced_by_subset() (in module trilearn.graph.junction_tree) support() (in module trilearn.graph.junction_tree_collapser) support_subtree_nodes() (in module trilearn.graph.junction_tree_collapser)

T

to_graph() (trilearn.graph.junction_tree.JunctionTree method) to_json() (trilearn.graph.empirical_graph_distribution.GraphDistribution method) (trilearn.graph.trajectory.Trajectory method) to_prufer() (in module trilearn.graph.junction_tree) tpr() (in module trilearn.auxiliary_functions) Trajectory (class in trilearn.graph.trajectory) trajectory_to_file() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) trajectory_to_queue() (in module trilearn.mh_greenthomas) (in module trilearn.pgibbs) trilearn.auxiliary_functions module trilearn.distributions module trilearn.distributions.dirichlet module trilearn.distributions.discrete_dec_log_linear module trilearn.distributions.g_intra_class module trilearn.distributions.g_inv_wishart module trilearn.distributions.gaussian_graphical_model module trilearn.distributions.matrix_multivariate_normal module trilearn.distributions.multivariate_students_t module trilearn.distributions.sequential_junction_tree_distributions module

trilearn.distributions.wishart module trilearn.graph.decomposable module trilearn.graph.empirical_graph_distribution module trilearn.graph.graph module trilearn.graph.greenthomas module trilearn.graph.junction_tree module trilearn.graph.junction_tree_collapser module trilearn.graph.junction_tree_expander module trilearn.graph.subtree_sampler module trilearn.graph.trajectory module trilearn.mh_greenthomas module trilearn.pgibbs module trilearn.set_process module trilearn.smc module true_distribution() (in module trilearn.graph.graph) tuple() (trilearn.graph.junction_tree.JunctionTree method) tuple_to_graph() (in module trilearn.graph.graph)

U

uniform_dec_maxl_clique_size_samples() (in module trilearn.smc)

uniform_dec_samples() (in module trilearn.smc) UniformJTDistribution (class in trilearn.distributions.sequential_junction_tree_distributions)

W

write_adjvec_trajectory() (trilearn.graph.trajectory.Trajectory method)

write_file() (trilearn.graph.trajectory.Trajectory method)